High-heeled shoes are a fashion staple in many women’s wardrobes. But wearing them too often is not only painful, it can be dangerous too. Not paying enough attention to your feet may lead to posture problems and foot deformities.
Today, we at Bright Side have prepared this infographic that will explain how to wear your favorite pumps and stilettos without killing your feet.
What are the attributes of an excellent medical school? How important are medical students’ scores on national exams, match rates for residency programs, or students’ decisions to practice in underserved areas? What about research productivity of faculty or the quality of care provided in the institution’s clinical facilities? All of these factors and more are important measures of excellence, and different medical schools will set different priorities for these and other important activities based on the schools’ histories, values, resources, and the current needs within their communities.
U.S. News and World Report has for years used a few measures, such as reputation, research activity, student selectivity, and faculty resources, in its annual rating system of medical schools.1 McGaghie and Thompson2 strongly criticized that rating system on methodological, conceptual, and ethical grounds and maintained that
the assessment of quality should be based on criteria … that go beyond wealth and reputation. They should be measures that are proven to be directly related to graduating better doctors.
They suggested six approaches to evaluating medical schools’ quality: accreditation, impact on students (e.g., their orientation to service), prosperity (the school’s financial health), public service, reputation, and research. And they ask, “Given accreditation … what is a medical school’s value added for its graduates?”
As examples of value added, they suggested increased inclusion of underrepresented minority students in a medical school’s classes, improved assessment of clinical skills, and service to the underserved as categories of importance. Mullan et al3 suggested that medical schools could be ranked based on their accomplishments in meeting the social mission of training physicians to care for the population as a whole, taking into account issues such as primary care, underserved areas, and workforce diversity. How important is the production of a workforce that will meet the needs of the population compared with other important goals? How are we to choose between so many different ideas of what constitutes excellence in medical education?
One approach might be to look at the most serious problems in our health system and how educational programs contribute to their causes and solutions. Rising health care spending with poor-quality outcomes is one such overarching problem.4 Health care spending in the United States reached 17.8% of the gross domestic product in 2016, far higher than that in 10 other high-income countries,5 yet the life expectancy in the United States was the lowest of the 11 countries at 78.8 years, and infant mortality was the highest (5.8 deaths per 1,000 live births). Papanicolas et al5 concluded that the high health care spending in the United States is driven by high prices for labor, pharmaceuticals, and administrative costs. Health care spending in the United States is projected to rise at an average rate of 5.5% per year from 2017–2026 and grow one percentage point faster than the gross domestic product.6
These statistics should concern health professions educators because they train the health professionals whose decisions about tests, procedures, and pharmaceuticals are part of the difference between health care costs in the United States and other advanced countries.7 Efforts to train students about using best evidence to select cost-effective treatments have been disappointing according to Ioannidis,8 who noted that evidence-based medicine (integrating individual clinical expertise with the best external evidence) has not led to more effective, efficient care. He asked, “How likely is it that physicians will design studies whose results may threaten their jobs by suggesting that less procedures, testing, interventions are needed?” Ioannidis points out the intrinsic conflicts of interest of physicians and hospitals, who benefit from the dollars spent in health care even as those same dollars become unavailable to communities and individuals for other important needs such as housing, transportation, or food. What, then, might health professions educators and academic health centers do to better meet the needs of the public for a high-quality and less costly health system?
I can suggest a possible direction by sharing a story. Some time ago I was working with a patient—whom I will call Tom Dolan—who had end-stage liver disease and recurrent fluid accumulations leading to tense ascites. He made frequent visits to the emergency department, often resulting in admissions to the hospital. Although he had appointments in the outpatient liver disease clinic, he had trouble getting there on time because of transportation problems and would come to the emergency department when his discomfort became intolerable. In one year, Mr. Dolan accumulated over $100,000 in medical bills from various admissions and procedures; most of the care was unreimbursed.
One day I was talking to our hospital administrator about this patient and wondering whether we could provide more social support and perhaps transportation to the liver clinic for him. I also mentioned that we had several other patients who received frequent care in the emergency department for chronic problems that could be better managed in an outpatient clinic if we could only provide transportation and social services and get the cooperation of the clinic staff and doctors. I also mentioned the effect Mr. Dolan had on the emergency department staff, who felt helpless to solve his underlying problems.
Our conversation ultimately led to an analysis of data and an initiative focusing on the care of high-cost patients like Mr. Dolan.9 This program involved the analysis of hospital billing data to identify high-cost patients with chronic illnesses, an initial physician and nursing assessment to develop a care plan, priority access to specialty clinics, social services and nurse case management, psychological support, and connection to primary care teams. The program resulted in reductions in costs and emergency department visits. However, in spite of these successes over 10 years, the lessons from this initiative have not become integrated into the medical school’s educational programs. The social challenges and chronic conditions of our patients were not as dramatic as the stimulating cases that illustrated pathophysiology in the problem-based learning classes or as the clinical problems of patients seen on clerkships.
Blumenthal et al10 have described efforts similar to ours at other academic medical centers to identify and manage high-cost patients, have encouraged the adoption of such programs more broadly, and have urged integrating the study of these initiatives into educational programs. It is interesting that as important as high-cost patients are to the financial success of health care providers, health plans, and government programs, there is little known about the attributes of these patients or how our educational systems might serve them. I believe that while this approach to cost saving has so far been a lost opportunity, it illustrates some of the potential that a careful analysis of the distribution of spending in health care can provide to our redesign of health professions educational programs.
Mitchell11 has shown that in 2014, 1% of the noninstitutionalized U.S. patients accounted for 22.8% of expenditures, with a mean of $107,208. At the same time, the bottom 50% of the U.S. population accounted for only 2.8%, or $264 dollars on average, of total health care spending. These are huge differences with implications for population management: That is, by understanding the characteristics of high-cost patients, how to identify them before they become high-cost ones, and how to prevent them from experiencing the events that lead to high cost, we might be able to eliminate or mitigate serious clinical—and associated—cost problems. Even if we were not able to prevent the initial high-cost events, we might be able to prevent future high costs for the same patients.
At the same time, by understanding that 50% of the patients spend little on health care, we could design programs to help keep them healthy with preventive services while making sure that they did not get offered unnecessary care that could raise overall population health costs without providing benefits. The patients who were in the middle of the cost pyramid could also be analyzed to understand what factors might move them up or down in their spending patterns. Health professions education focuses on the diagnosis and treatment of high-cost patients but not on early recognition and prevention of conditions that can lead to high costs. What if excellence in health professions education recognized the importance of preparing a workforce that could recognize and change the trajectory of a serious illness rather than demonstrating procedural competence for treatments that might not have been needed?
Johnson et al12 identified a group of patients in Denver who were super users of health care, with an average annual spending of $113,522, and found them to cluster in diagnostic and social groupings such as patients with multiple chronic diseases, terminal cancer patients, recipients of emergency inpatient dialysis, trauma patients, individuals with serious mental health diagnoses, and orthopedic surgery patients. Recipients of emergency dialysis might not even need the dialysis on an emergency basis if financial and political barriers could be overcome; similar convenience and economy could certainly be achieved for at least some of the other groups. The approaches to reducing the spending for these patients would differ depending on the diagnostic/social group, and health professions education that fostered skills of data analysis and health policy advocacy might improve the quality of care and reduce the costs for segments of the population.
Dow et al13 have described a segmentation of their institution’s patient population based on cost and types of chronic conditions and the implications for the health professions workforce. Education of interprofessional teams to manage groups of patients could be a sign of care delivery and educational excellence. Lipstein et al14 have further developed recommendations for the health workforce, based on the perceived future needs of the population, that would involve the development of teams that could address both social and health-care-related problems. Meltzer and Ruhnke15 have described ambulatory physicians who manage high-risk, high-cost patients; these physicians could lead teams of caregivers. The skills needed by such teams would likely overlap with those needed in primary care and would provide a unique skill set to coordinate specialists, social care systems, nursing, and pharmacy services. Current payment models do not adequately reimburse physicians who spend time helping to avoid a hospitalization by arranging alternative approaches to care for complex patients like Mr. Dolan, but if payments shifted away from a fee-for-service model to a population management approach, there could be more financial support for the kind of physicians described by Meltzer and Ruhnke.
How might current health professions educational programs enlarge their perspective to address the needs of populations? While medical schools have different missions, with some focused on training clinician scientists and others oriented toward primary care for underserved populations, the acknowledgment of social accountability of medical education to address workforce needs would be an important step. Canada has adopted a social accountability goal for medical education. The Association of Faculties of Medicine16 noted the need for a national approach to physician resource planning and that
medical schools collaborate with the federal, provincial, and territorial governments and other national medical educational and licensing bodies to ensure the right number and mix of physicians entering practice.
By matching the population health needs with production of the right mix of health professionals who have the right set of skills, health care spending and quality of care could be vastly improved.
While the United States has struggled to find a consensus on health insurance and health care systems, the growing support for competency-based medical education might provide the opportunity to focus on population health management for medical students and residents. Gourevitch17 has described the way in which population health education and research could be integrated into an academic medical center to create a competency in population health management. However, adding more competencies to the growing list of competencies has drawbacks, as noted by Norman et al18 in their critique of competency-based medical education. The addition of any new competencies could create an unmanageable list that could dilute the importance of all of them and be unacceptable.
Another option would be to identify those organizations and projects that are already leading in developing population management programs and work with them to learn what knowledge and skills their teams require. This would encourage the development of educational programs, and the education would be specific to the clinical needs of specific populations. Bodenheimer and Berry-Millett19 provide examples of organizations and projects that are models of how to reorient the care delivery system to manage high-cost patients in an efficient, high-quality way. There are others, as noted by Blumenthal et al.10 Financial incentives that would encourage population segmentation and chronic care management, including the funding of interprofessional teams, could nurture the spread of innovative care models and the educational programs needed to support them. Education might begin with continuing professional development of practicing physicians and diffuse into the graduate and undergraduate medical systems as necessary prerequisites for employment.
We could also follow the lead of Gonzalo et al20 to establish health systems sciences as a third and coequal branch of medical education, joining basic sciences and clinical sciences as a foundational building block of medicine. In this way, the preparation of a health workforce interested in population health and trained to manage health spending would be a part of the education of every medical student and other health professions students. The success of the medical school and its rating for excellence would partly depend on the effectiveness of its education and care in health systems sciences, which would include population management. If we did this, the models of care that demonstrated success in meeting population health goals would be integrated into the curriculum. By better aligning the educational and care delivery goals, decisions about curricular change could be made in a logical and consistent manner.
While I am skeptical of medical school ratings, if such ratings are to have any value at all, they must include recognition of medical schools that train students and residents with population health skills and that motivate trainees to reduce health care spending, narrow disparities in care, improve health care quality, and provide access to care for our underserved populations. And while we are considering recognition of medical schools, we should include those that reduce or do not require tuition, such as New York University School of Medicine, which recently eliminated tuition. Lifting this great financial burden could influence medical students to more favorably consider practicing in underserved locations and choosing specialties most needed for improving the health of the public.
PATIENT NUMBER TWO was born to first-time parents, late 20s, white. The pregnancy was normal and the birth uncomplicated. But after a few months, it became clear something was wrong. The child had ear infection after ear infection and trouble breathing at night. He was small for his age, and by his fifth birthday, still hadn’t spoken. He started having seizures. Brain MRIs, molecular analyses, basic genetic testing, scores of doctors; nothing turned up answers. With no further options, in 2015 his family decided to sequence their exomes—the portion of the genome that codes for proteins—to see if he had inherited a genetic disorder from his parents. A single variant showed up: ARID1B.
The mutation suggested he had a disease called Coffin-Siris syndrome. But Patient Number Two didn’t have that disease’s typical symptoms, like sparse scalp hair and incomplete pinky fingers. So, doctors, including Karen Gripp, who met with Two’s family to discuss the exome results, hadn’t really considered it. Gripp was doubly surprised when she uploaded a photo of Two’s face to Face2Gene. The app, developed by the same programmers who taught Facebook to find your face in your friend’s photos, conducted millions of tiny calculations in rapid succession—how much slant in the eye? How narrow is that eyelid fissure? How low are the ears? Quantified, computed, and ranked to suggest the most probable syndromes associated with the facial phenotype. There’s even a heat map overlay on the photo that shows which the features are the most indicative match.
“In hindsight it was all clear to me,” says Gripp, who is chief of the Division of Medical Genetics at A.I. duPont Hospital for Children in Delaware, and had been seeing the patient for years. “But it hadn’t been clear to anyone before.” What had taken Patient Number Two’s doctors 16 years to find took Face2Gene just a few minutes.
Face2Gene takes advantage of the fact that so many genetic conditions have a tell-tale “face”—a unique constellation of features that can provide clues to a potential diagnosis. It is just one of several new technologies taking advantage of how quickly modern computers can analyze, sort, and find patterns across huge reams of data. They are built in fields of artificial intelligence known as deep learning and neural nets—among the most promising to deliver AI’s 50-year old promise to revolutionize medicine by recognizing and diagnosing disease.
In validation studies done by the test’s inventor, UC San Diego researcher Karen Pierce,1the test correctly predicted autism spectrum disorder 86 percent of the time in more than 400 toddlers. That said, it’s still pretty new, and hasn’t yet been approved by the FDA as a diagnostic tool. “In terms of machine learning, it’s the simplest test we have,” says RightEye’s Chief Science Officer Melissa Hunfalvay. “But before this, it was just physician or parent observations that might lead to a diagnosis. And the problem with that is it hasn’t been quantifiable.”
A similar tool could help with early detection of America’s sixth leading cause of death: Alzheimer’s disease. Often, doctors don’t recognize physical symptoms in time to try any of the disease’s few existing interventions. But machine learning hears what doctor’s can’t: Signs of cognitive impairment in speech. This is how Toronto-based Winterlight Labs is developing a tool to pick out hints of dementia in its very early stages. Co-founder Frank Rudzicz calls these clues “jitters,” and “shimmers:” high frequency wavelets only computers, not humans, can hear.
Winterlight’s tool is way more sensitive than the pencil and paper-based tests doctor’s currently use to assess Alzheimer’s. Besides being crude, data-wise, those tests can’t be taken more than once every six months. Rudzicz’s tool can be used multiple times a week, which lets it track good days, bad days, and measure a patient’s cognitive functions over time. The product is still in beta, but is currently being piloted by medical professionals in Canada, the US, and France.
If this all feels a little scarily sci-fi to you, it’s useful to remember that doctors have been trusting computers with your diagnoses for a long time. That’s because machines are much more sensitive at both detecting and analyzing the many subtle indications that our bodies are misbehaving. For instance, without computers, Patient Number Two would never have been able to compare his exome to thousands of others, and find the genetic mutation marking him with Coffin-Siris syndrome.
But none of this makes doctors obsolete. Even Face2Gene—which, according to its inventors, can diagnose up to half of the 8,000 known genetic syndromes using facial patterns gleaned from the hundreds of thousands of images in its database—needs a doctor (like Karen Gripp) with enough experience to verify the results. In that way, machines are an extension of what medicine has always been: A science that grows more powerful with every new data point.
A study of men who were evaluated for the cause of their infertility finds previously unknown relationships between deficiencies in their semen and other, seemingly unrelated health problems.
A study of more than 9,000 men with fertility problems has revealed a correlation between the number of different defects in a man’s semen and the likelihood that the man has other health problems.
The study, conducted by investigators at the Stanford University School of Medicine, also links poor semen quality to a higher chance of having various specific health conditions, such as hypertension, and more generally to skin and endocrine disorders.
The findings, published online Dec. 10 in Fertility and Sterility, may spur more-comprehensive approaches to treating male infertility. They also point to the wisdom of performing complete physical examinations of men experiencing reproductive difficulties.
“About 15 percent of all couples have fertility issues, and in half of those cases the male partner has semen deficiencies,” said the study’s lead author, Michael Eisenberg, MD, assistant professor of urology and director of male reproductive medicine and surgery at Stanford. “We should be paying more attention to these millions of men. Infertility is a warning: Problems with reproduction may mean problems with overall health.”
A study Eisenberg co-authored a few years ago showed that infertile men had higher rates of overall mortality, as well as mortality linked to heart problems, in the years following an infertility evaluation. “But here, we’re already spotting signs of trouble in young men in their 30s,” he said.
Analyzing medical records
In the new study, Eisenberg and his colleagues analyzed the medical records of 9,387 men, mostly between 30 and 50 years old, who had been evaluated at Stanford Hospital & Clinics (now Stanford Health Care) between 1994 and 2011 to determine the cause of their infertility. The men had routinely provided semen samples, which the researchers assessed for characteristics including volume, concentration and motility. In about half of all the male infertility cases, the problem was abnormal semen; in the rest, the fault lay elsewhere. So, using the database, the investigators were able to compare the overall health status of men who had semen defects to that of the men who didn’t.
With a median age of 38, this was a fairly young group of men. However, 44 percent of all the men had some additional health problem besides the fertility problem that brought them to the clinic. In particular, the investigators found a substantial link between poor semen quality and specific diseases of the circulatory system, notably hypertension, vascular disease and heart disease. “To the best of my knowledge, there’s never been a study showing this association before,” said Eisenberg. “There are a lot of men who have hypertension, so understanding that correlation is of huge interest to us.”
In addition, as the number of different kinds of defects in a man’s semen rose, so did his likelihood of having a skin disease or endocrine disorder. When looking at the severity of all health problems, the scientists observed a statistically significant connection between the number of different ways in which a man’s semen was deficient and the likelihood of his having a substantial health problem.
Health, semen quality ‘strongly correlated’
The study wasn’t designed to determine precisely how connections between semen deficiencies and seemingly unrelated disorders, such as cardiovascular or endocrine disease, come about. But, Eisenberg noted, some 15 percent of all genes in the human genome are connected fairly directly to reproduction, and most of these genes also have diverse functions in other bodily systems. He also noted that it may not be a disease itself, but the treatment for the disease, that’s actually responsible for reproductive malfunction. He said he is exploring this possibility now.
As we treat men’s infertility, we should also assess their overall health.
“A man’s health is strongly correlated with his semen quality,” he said. “Given the high incidence of infertility, we need to take a broader view. As we treat men’s infertility, we should also assess their overall health. That visit to a fertility clinic represents a big opportunity to improve their treatment for other conditions, which we now suspect could actually help resolve the infertility they came in for in the first place.”
The senior author of the study is Mark Cullen, MD, professor of medicine at Stanford. Other Stanford co-authors are professor of reproductive endocrinology and fertility Barry Behr, PhD; former professor of obstetrics and gynecology Renee Reijo Pera, PhD; and statistical programmer Shufeng Li.
Story Source:
The above story is based on materials provided by Stanford University. Note: Materials may be edited for content and length.
Journal Reference:
Today, humans suffer from a wide range of diseases and disorders that didn’t exist in the past, a trend that will likely continue well into the future. Here are 10 unexpected and wholly unpleasant diseases we’ll eventually have to contend with.
It’s impossible to know which pathogens will afflict us in the future, but by looking at technological and social trends, we can make some educated guesses about the kinds of diseases and disorders that are likely to emerge.
Consider this your speculation warning. We’re about to journey out of what we do know, into the realm of what might happen.
Deliberate acts of bioterrorism and biohacking will introduce entirely new and unexpected problems, such as the deliberate dissemination of bioengineered viruses or brain hacking. But for the purposes of this list, I’ve chosen to exclude those possibilities. I’ll set those aside for a future io9 superlist. This post will only consider health issues that are likely to emerge as a consequence of our technological advancements and our inability to cope with them.
Remember that episode of ST-TNG when Lieutenant Reginald Barclay became hopelessly obsessed with the Holodeck? Given how much better his make-believe world was compared to his drab life, you can’t really blame him. Indeed, virtual reality will introduce us to environments and settings far more compelling — and far more controllable than real life.
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Once fully immersive VR becomes available, it’ll become increasingly difficult for people to engage with reality. What’s more, because VR will offer the opportunity for people to physically interface with their friends and colleagues across vast distances, and with a dizzying array of technological features at their disposal, it’ll become increasingly difficult and inconvenient to detach. Consequently, virtual reality withdrawal will become a common and serious problem. We’re already seeing the signs of this today in the form of so-called Internet Addiction Disorder (IAD) and Internet Gaming Disorder (IGD). Relatedly, psychologists have already had to treat a person for IAD caused by overuse of Google Glass.
On a related note, virtual reality will eventually become so believable and so realistic that it’ll be next to impossible for a person to distinguish their virtual experiences from those in the real world.
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People suffering from this disorder will be incessantly racked by doubt as to whether a particular modal reality represents the real universe or if it’s a sophisticated copy of reality (interestingly, as these lines begin to blur, this distinction will become increasingly unimportant).
This disorientation will likely extend to interpersonal interactions as well — a condition of doubt in which people will not be able to tell whether they’re interacting with a “real” virtual person, or just a sophisticated bot.
As time passes, and as strange as this sounds, it’ll become increasingly difficult to know who — or even what — we are.
We’re increasingly offloading and segmenting our brain’s cognitive processes to the Internet. Our artificially intelligent personal assistants will work on our behalf to perform odd jobs and other functions delegated to them. By consequence, they’ll start to assume our identities in proxy. These cloud exoselves will learn from us and behave exactly the way we do. Eventually however, either by hard or soft uploading, we’ll join them in cyberspace, leading to a potential identity crisis. It will become increasingly challenging to discern which part of the cloud is truly us, and which is not. It’s a problem that’s sure to be compounded by having multiple personas, some of which live full and distinctive lives in alternate environments. Consequently, we won’t know where we start and where we end, leading to a total loss of individuality and pathological confusion about our true selves.
Imagine waking up from cryostasis hundreds or thousands of years from now and trying to integrate into whatever uber-futuristic society you’ve been plopped into.
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Depending on how your frozen body was reanimated, you may find that you’ve suddenly become a highly advanced cyborg living among speciated humans and posthumans of all types. Alternately, you could wake to find that you’re no longer corporeal, living as some kind of virtual being in an elaborate supercomputer simulation.
Regardless, it’ll be a wholly unpleasant and distressing experience. You won’t know anyone, and you won’t have a clue about your new physical and cognitive skills. Nor will you have any inkling about new technologies, your new society, or culture. What’s more, you may not even like your new life. It’ll be a kind of future shock, but nothing like Alvin Toffler could have ever predicted. To help you cope, your new benefactors could upload everything you need to know directly into your brain, or they could place you into some kind of re-integration class.
We’re not entirely sure how our bodies will react to cybernetic implants over time, or the kinds of health problems they’ll introduce.
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Some implants may cause severe allergic reactions or exaggerated immune responses. Complications could arise in the way implants interact with tissues surrounding it, including infection, inflammation, and pain. They could also interfere with normal bodily functioning. There’s also risk of rejection. Additionally, these implants could start to decay and degrade in unexpected ways, leading to life-threatening toxic effects and various forms of infections.
Nanotechnology has the potential to reshape virtually every aspect of the human condition, both for better and for worse. Already today, scientists are concerned about the impact that nanotechnological materials and devices will have on the environment. There’s considerable debate as to what extent industrial and commercial use of nanomaterials will affect organisms and ecosystems.
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Because these technologies involve the production of materials at the molecular scale, it’s conceivable that particulate matter will begin to bioaccumulate in the environment. Humans will eventually come into contact with these nanopollutants, causing all sorts of serious health problems, including damage to our cells and DNA.
On a related note, nanotechnological devices that are deliberately infused into the human bodycould cause serious problems as well. Poorly designed nanobots could deliver medicines to the wrong area, or degrade in unpredictable ways. And if their programming goes awry, they could physically damage tissue, or replicate uncontrollably, leading to an internal grey goo catastrophe. And like cybernetic implants, they could also trigger exaggerated immune responses resulting in anaphylactic shock.
Our society fetishizes intelligence, so it’s likely that we’ll start to boost our cognitive abilities using any number of biotechnologies, including genomics, nootropics, and cybernetics.
Trouble is, our culture is biased towards a very narrow band of intelligence — namely “IQ-type” intelligence, or what Mark Changizi calls chess-and-brain-teaser-like intelligence. But the acquisition of extreme cognitive abilities could prove to be maladaptive. Our evolutionarily-calibrated psychologies may not be able to handle such out-of-bounds intelligence. Should you choose to augment your brain, you may start to exhibit antisocial behaviors and outright insanity, including such behaviors and problems as pattern seeking (a la John Nash), seizures, information overload, anxiety attacks, existential crises, egomania, and extreme alienation.
In the future, some of us may develop an irrational and exaggerated fear of robots.
This psychological disorder will skirt the line between a true phobia and mere prejudice, particularly as robots become more fully integrated into society, as they assume our jobs — and as they progressively become more powerful and human-like in their behavior.
The sex chip is coming — the ability to trigger feelings of extreme pleasure on demand. Sure, sounds great in principle, but most of us don’t have the willpower to use it on a selective basis.
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Back in 2008, neuroscientists Morten Kringelbach and Tipu Aziz announced that they were able to stimulate the pleasure centers of the brain by implanting a chip that sends tiny shocks to the orbitofrontal cortex, the area responsible for feelings of pleasure.
Experiments have shown that rats would rather starve than give up the ability to flip a reward switch. And as the case of a woman addicted to her thalamic stimulator attests, self-stimulation can quickly become habitual. It would be like the ST:TNG episode “The Game” come to life, and it would introduce what science fiction author Larry Niven referred to as “wireheads.” Once sex chips become commonplace, expect to see this one written-up in a future version of the DSM.
Once we conquer aging, some of us might get bored living an indefinitely long life. But I doubt it. What’s more likely is something a bit more existential — a general tiring of life itself, a related emotional condition known as ennui.
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Super-elderly people living in such a state would find everything bland and hyper-repetitive. Barring interventions, nothing would seem exciting or novel anymore. It would be like something John Cougar Mellencamp once said, “Life goes on long after the thrill of living is gone.” Such feelings could become endemic, leading to a broader social health crisis.
Story at-a-glance
- “Metabolically healthy” overweight or obesity describes people who are carrying excess weight without any of the corresponding health problems
- A large meta-analysis revealed “healthy obesity” may be a myth
- The review found that obese individuals were more likely to die sooner or have heart-related problems than people of normal weight – even if they were otherwise healthy
- Separate research suggested that seemingly healthy obesity may be a transient state, with health problems coming down the road
- Most overweight Americans have some degree of insulin and leptin resistance that can be addressed by making dietary changes and exercising
In the last decade, researchers have been exploring the paradox of “metabolically healthy” overweight or obesity, which describes people who are carrying excess weight without any of the corresponding health problems that typically go along with it.
Is it possible to be overweight or obese and healthy? Yes, just as it’s possible to be normal weight and unhealthy. But is it likely? Probably not, according to the latest research.
Last year, data from nearly three million adults suggested that having an overweight body mass index (BMI) may be linked to a longer life than one that puts you within a “normal” weight range.
The research, which analyzed 97 studies in all, found that people with BMIs under 30 but above normal (the overweight range) had a 6 percent lower risk of dying from all causes than those who were normal weight, while those whose BMIs fell into the obese range were 18 percent more likely to die of any cause.1
There were problems with this study, however, as there often are in those that seem to show a positive effect of obesity. For instance, it doesn’t tell you whether those living longer were afflicted with more chronic disease or whether their quality of life was otherwise impacted.
And even more importantly, it used only BMI as a measure of body composition, and this is a highly flawed technique in determining if a person is truly obese and it fails to differentiate between muscle and fat tissue.
Many studies, such as one published in the Journal of the American College of Cardiology,2 have actually found that a high BMI was associated with a lower risk of death, a phenomenon known as the “obesity paradox.” But these findings are typically only examples of how BMI is such a flawed measurement tool.
Still, other research published last year also tried to find out whether metabolically healthy obesity was a myth, and revealed that it appeared to be a “transient state” for one-third of the study participants.3 In other words, many who appear to be healthy will end up with health problems down the road.
Not surprisingly, those who continued to be metabolically healthy and obese were younger and had a smaller waist circumference. However, the latest research, which may be the most comprehensive to date, suggests that metabolically healthy obesity simply doesn’t exist.
This was a recent headline from TIME, describing the results of a new Annals of Internal Medicine4 study, which concluded that there’s no such thing as being “healthy” and obese.
The study, a systematic review and meta-analysis that included data from more than 61,000 people, found that obese individuals were more likely to die sooner or have heart-related problems than people of normal weight – even if they were otherwise healthy. The researchers concluded:
“Compared with metabolically healthy normal-weight individuals, obese persons are at increased risk for adverse long-term outcomes even in the absence of metabolic abnormalities, suggesting that there is no healthy pattern of increased weight.”
As for why past studies have supported the notion that you can be fit and fat, the featured study’s lead author pointed out several problems with how some of the studies were set up:5
- Some studies only looked at risk of adverse events, rather than measures of metabolic health. So if an overweight person avoided an adverse event during the study, they could be classified as healthy even though they may have had underlying signs of diabetes or high blood pressure that the study didn’t look for.
- Some studies compared healthy obese people to unhealthy obese people, instead of comparing them to healthy normal-weight people.
- Some studies only used small groups of participants or short time periods, which may have missed problems in larger populations or that occur over time
It should be noted that the study did not find an increased risk of death or cardiovascular problems among those who were overweight and metabolically healthy, compared to those of normal weight and metabolic health. However, it did reveal that everyone with poor metabolic health had increased risk, regardless of their weight status.
Please realize that you can have metabolic dysfunction and be prone to obesity-related diseases even if your bodyweight is fine. This is one more reason why you can’t rely on your BMI alone, as it won’t give you the complete picture of your health.
However, according to the featured study, health risks did go up as BMI increased, which suggests that as your weight creeps up, so to do your health risks. And even if you’re healthy now, that might not be true for long. As the Los Angeles Timesreported:6
“When researchers used BMI to line up all of the 61,386 subjects who participated in the eight studies they pooled, they found that, as BMI rose, so rose blood pressure, waist circumference and insulin resistance.
As BMI increased, levels of HDL cholesterol, thought to protect against heart attack and stroke, decreased. Though overweight and obese subjects may not yet have reached the points that define metabolic illness, they appeared to be on that road as their weight rose.”
Obesity itself is rarely listed as a cause of death. Instead, the complications of obesity, such as heart disease or diabetes, are blamed for a person’s death. If you are obese, your risk for a number of serious health problems multiplies.
Obesity-related illness is predicted to raise national health care costs by $48 billion annually over the next two decades by adding another 7.9 million new cases of diabetes, 5 million cases of chronic heart disease and stroke, and 400,000 cancer cases.7 Eight obesity-related diseases account for a staggering 75 percent of healthcare costs in the US. These diseases include:
Type 2 diabetes Non-alcoholic fatty liver disease (NAFLD) Hypertension Polycystic ovarian syndrome Lipid problems Cancer (especially breast, endometrial, colon, gallbladder, prostate, and kidney8) Heart disease Dementia
The four diseases in the left column are associated with metabolic syndrome, which is a common factor in obesity. However, several other diseases fall within this category as well, which are listed on the right. And many more could be added to that list. According to the Surgeon General, in addition to the diseases mentioned above, obesity increases your risk for asthma, sleep disorders (including sleep apnea), depression, pregnancy complications, and poor surgical outcomes.9
While obesity is associated with metabolic syndrome and the diseases mentioned above, it is not their cause; it is simply a marker. The common link among them ismetabolic dysfunction, and excessive sugar/fructose consumption is a primary driver. Even if you don’t yet have clinical signs of metabolic dysfunction, the fact that you’re gaining excess weight is sign enough.
You see, most overweight Americans have some degree of insulin and leptin resistance. Generally, in order for you to significantly gain weight, you must first become leptin resistant. Leptin is a hormone that helps you regulate your appetite. When your leptin levels rise, it signals your body that you’re full, so you’ll stop eating.
However, as you become increasingly resistant to the effects of leptin, you end up eating more. Many people who are overweight also have an impairment in their body’s ability to oxidize fat, which leads to a low-energy state. Dr. Richard Johnson’s researchclearly shows that refined sugar (in particular fructose) is exceptionally effective at causing leptin resistance in animals, and it’s very effective at blocking the burning of fat.
If you are insulin or leptin resistant, as long as you keep eating fructose and grains, you’re programming your body to create and store fat…This is one of the key reasons why, if you are overweight (which means you are also likely insulin or leptin resistant), it would be prudent for you to restrict your fructose consumption to about 15 to 25 grams of fructose per day from all sources. Not only will this help you to avoid additional weight gain, it will also help you to avoid further metabolic dysfunction. You may find thisfructose chart helpful in estimating how many grams of fructose you are consuming each day.
Using BMI to gauge obesity is a seriously flawed index that doesn’t take into account your percentage of body fat or thedistribution of that fat. When those variables are factored in, the number of people who meet the criteria for obesity is MUCH higher—possibly even twice as high! As far as simple indicators go, waist to hip ratio is a better predictor of heart disease risk than body weight or BMI. A large waist size is a powerful predictor of being unhealthy because it is a sign that you have too much intra-abdominal or visceral fat that surrounds your liver, kidneys, intestines, and other organs. This is also known as the classic apple-shaped obesity. Thankfully, this is also one of the first signs that will change as a result of your program. So before you start your weight loss program, get a tape measure and record your waist and hip circumference.
Waist to Hip Ratio Men Women Ideal 0.8 0.7 Low Risk <0.95 <0.8 Moderate Risk 0.96-0.99 0.81 – 0.84 High Risk >1.0 >0.85
You can also use body-fat calipers or a digital scale that determines body fat to figure out your body fat percentage. Although many body fat measurements can be inaccurate, they are nearly all more accurate than BMI, and are particularly useful to determine whether you are gaining or losing fat. Although the absolute value may be off, the direction you are going (whether your body fat is going up or down) will be very accurate, and this is an incredibly useful measure of whether you’re nearing your health goals or not. A general guideline from the American Council on Exercise is as follows:10
Classification Women (percent fat) Men (percent fat) Essential Fat 10-13 percent 2-5 percent Athletes 14-20 percent 6-13 percent Fitness 21-24 percent 14-17 percent Acceptable 25-31 percent 18-24 percent Obese 32 percent and higher 25 percent and higher
Dietary sugar, especially fructose, is a significant “tripper of your fat switch,” which is why, if you are serious about losing weight, you’ll need a comprehensive plan that includes the following. This plan will help most people lose weight but, also, it will help you to gain metabolic health. So even if your weight is normal, you can follow this plan to ensure that you’re metabolically healthy as well.
- Eliminating or strictly limiting fructose in your diet, and following the healthy eating program in my comprehensive nutrition plan.
- You can also use intermittent fasting strategically with this program to greatly boost your body’s fat-burning potential.
- Engaging in high-intensity Peak Fitness exercise to burn fat and increase muscle mass (a natural fat burner).
- Addressing the emotional component of eating. For this I highly recommend the Emotional Freedom Technique (EFT), which helps eliminate your food cravings naturally.
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